
Data Pipeline Specialist
2 days ago
Job Summary
We are seeking a highly skilled Data Engineer to design, build and maintain large-scale data pipelines. This individual will work with streaming data, collaborate with data scientists and stakeholders to deliver high-quality solutions.
Key Responsibilities:
Design and optimize complex data pipelines using Spark and ETL workflows.
Manage and process massive datasets using Spark, PySpark and SQL.
Build and maintain real-time streaming applications with Spark Streaming/Kafka.
Collaborate with data scientists to integrate AI/ML models into production environments.
Ensure data quality, scalability and performance in all pipelines.
Deploy and manage Spark workloads on cloud platforms (AWS, Azure, GCP, Databricks).
Automate testing and deployment of Spark jobs via CI/CD pipelines.
Requirements:
Bachelor's/Master's degree in Computer Science, Computer Engineering or related field.
Minimum 4 years of professional experience as a Data Engineer.
Strong expertise in Python, Spark, PySpark.
Hands-on experience with Spark SQL, DataFrames, UDFs, DAG execution.
Knowledge of data ingestion tools (Kafka, Flume, Kinesis) and data formats (Parquet, Avro, ORC).
Proficiency in Airflow/Prefect for scheduling and orchestration.
Familiarity with performance tuning in Spark (partitioning, caching, broadcast joins).
Experience deploying on Databricks, AWS EMR, Azure HDInsight or GCP Dataproc.
Exposure to testing and CI/CD for data pipelines (pytest, Jenkins, GitHub Actions).
Why You'll Love This Role
This position offers the opportunity to work on challenging projects, develop skills in data engineering and contribute to business growth.
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